The Clinical Implementation of NEWS, SOFA, and CALL Scores in Predicting the In-Hospital Outcome of Severe or Critical COVID-19 Patients

Objective: To date, there is no specific validated coronavirus disease 2019 score to assess the disease severity. This study aimed to evaluate the performance of the National Early Warning Score, Sequential Organ Failure Assessment, and Comorbidity-Age-Lymphocyte count-Lactate dehydrogenase scores in predicting the in-hospital outcome of critical or severe coronavirus disease 2019 patients. Materials and Methods: Single-centered analytical study was carried out in the coronavirus disease 2019 high dependency unit from April to August 2020. National Early Warning Score, Sequential Organ Failure Assessment, and Comorbidity-Age-Lymphocyte count-Lactate dehydrogenase scores were calculated for each critical to severely ill coronavirus disease 2019 patient. The diagnostic accuracy of these 3 scores in determining the in-hospital outcome of coronavirus disease 2019 patients was assessed by area under the receiver operating characteristic curve. The cut-off value of each score along with sensitivity, specificity, and positive and negative likelihood ratio were calculated by Youden index. Predictors of outcome in coronavirus disease 2019 patients were analyzed by Cox-regression analysis. Results: The area under the curve was highest for the Comorbidity-Age-Lymphocyte count-Lactate dehydrogenase score (area under the curve = 0.85) while the Sequential Organ Failure Assessment score had an area under the curve of 0.72. The cut-off values for National Early Warning Score score was 8 (sensitivity = 72.34%, specificity = 76.10%), Sequential Organ Failure Assessment score was 3 (sensitivity = 68.97%, specificity = 67.42%), and Comorbidity-Age-Lymphocyte count-Lactate dehydrogenase score was 8 (sensitivity = 88.89%, specificity = 66.67%). The pairwise comparison showed that the difference between the area under the curve of these 3 scores was statistically insignificant (P > .05). The rate of mortality and invasive ventilation was significantly high in groups with high National Early Warning Score, Sequential Organ Failure Assessment, and Comorbidity-Age-Lymphocyte count-Lactate dehydrogenase scores (P < .0001). These 3 scores, age, low platelets, and high troponin-T levels were found to be statistically significant predictors of outcome Conclusion: Comorbidity-Age-Lymphocyte count-Lactate dehydrogenase score had a good area under the curve, the highest sensitivity of its cut-off value, required only 4 parameters, and is easy to calculate so it may be a better tool among the 3 scores in outcome prediction for coronavirus disease 2019 patients.


Introduction
Coronavirus disease 2019 (COVID-19) infection has posed this century' s greatest challenge to humanity. With its emergence as an unexplained viral illness in Wuhan in December 2019, it spread enormously to the rest of the world. 1 So far, COVID-19 has resulted in thousands of deaths globally. Although COVID-19 infection exhibits itself as mild upper respiratory symptoms like flu and cold-like symptoms in many patients, in others, it can present as severe respiratory tract illness or even have a fatal outcome. 2,3 A mortality rate of 11%-62% among severely affected or critical patients with COVID-19 has been reported. 4 With an increase in the number of COVID-19 victims and a lack of health care resources, it has become difficult to effectively manage these patients. 5 Henceforth, triaging high-risk patients at the earliest instance and ensuring their timely access to medical intervention are of paramount importance in reducing morbidity and mortality. There are a number of parameters that were utilized initially to assess disease severity such as white blood cell count, d-dimers, and interleukin 6 levels. 6 But none of these alone would serve as a definitive marker of disease severity and poor outcome. Similarly, there is no specific validated COVID-19 severity score in place to date. To overcome this difficulty, various centers have utilized a number of pre-existing early warning scores (EWS) used to triage patients in the emergency department. 7 Notable among these EWS are National Early Warning Score (NEWS) and Modified Early Warning Score (MEWS). 8,9 Similarly, Sequential Organ Failure Assessment (SOFA) score and Comorbidity-Age-Lymphocyte count-Lactate dehydrogenase (CALL) score are also utilized. 10,11 At present numerous studies exist that assess these EWS in emergency settings. With regards to COVID-19 patients, not many studies exist that have effectively used these EWS as a predictor of patient outcome. In keeping with the lack of a validated COVID-19-specific severity assessment tool, we need to probe into the existing ones to make use of a good one among them. Therefore, the rationale of our study was to evaluate the performance of these indicators (NEWS, SOFA, and CALL scores) calculated at the time of admission in predicting in-hospital outcome of patients with critical or severe COVID-19 infection.

Study Design and Settings
Single-centered analytical cross-sectional study was carried out in the COVID-19 high dependency unit (COVID-19 HDU) of Fauji Foundation Hospital, Rawalpindi from Mid-April 2020 to the last week of August 2020. Fauji Foundation Hospital Rawalpindi is a large 850-bedded tertiary care hospital that was established to serve the families of retired armed people. This hospital established HDU in response to the COVID-19 pandemic which was fully equipped with all the necessary advanced facilities (invasive mechanical ventilation, continuous and bi-level airway positive pressure, 24-hour continuous oxygen delivery to patients through mask, nasal prongs, or rebreather masks), all investigational therapies (therapeutic plasmapheresis and convalescent plasma therapy), and availability of investigational pharmacological agents (remdesivir, tocilizumab, etc.) for management of severe to critical COVID-19 patients admitting in HDU.
The main objective was to evaluate the efficacy of 3 scoring systems (NEWS, SOFA, and CALL scores) calculated at the time of admission in determining the outcome of patients with severe or critical COVID-19 infection.

Characteristics of Study Participants
This study included the following patients: 1. Patients aged >13 years with reverse transcription-polymerase chain reaction confirmed COVID-19 infection and were admitted to COVID-19 HDU due to critical or severe disease. 2. Patients with infiltrates >50% on chest x-ray ± High Resolution CT chest (HRCT) chest suggestive of extensive peripheral ground glass opacities ± blood pressure (BP) <90 mmHg with Heart rate (HR) >100/min ± respiratory rate (RR) >30/min ± SpO 2 <90% (severe disease category). 3. Patients with evidence of acute respiratory distress syndrome or cytokine release syndrome or septic shock ± multi-organ involvement (critical disease category).
The patients aged <13 years and patients who died within 24 hours (provided their laboratory tests were not done) were excluded from the study (n = 11).
NEWS, SOFA, and CALL Scores 1. National Early Warning Score was calculated by 7 parameters (respiratory rate, oxygen saturation, supplemental oxygen, systolic BP, pulse, temperature, and level of consciousness). 12 2. Sequential Organ Failure Assessment score was calculated by 7 parameters (PaO 2 /FiO 2 level, platelet count, bilirubin, creatinine, Glasgow Coma Score, mean BP + administration of vasoactive agents and mode of oxygen delivery, Continuous positive airway pressure (CPAP) or invasive ventilation. 13 3. Comorbidity-Age-Lymphocyte count-Lactate dehydrogenase score was calculated by 4 parameters (age, co-morbidities, lactate dehydrogenase, and platelet count) (Supplementary Material NEWS score). 14

Methodology
The hospital developed a policy at the time of establishing COVID-19 HDU that when admitted to COVID-19 HDU, informed written consent would be signed by every patient or their relative that clinical, laboratory, and biochemical data of patients can be utilized for COVID-19-related research purposes with the following aims: a. to provide benefit to patients all over the world suffering from this disastrous disease, b. to share the experience of doctors of this hospital with other institutes of this country as well as other countries, c. to outline the effective treatment strategy of patients for management of COVID-19 infection by retrospective analyzing the collected data, and d. to update this treatment strategy time by time.
The privacy of each patient was maintained throughout the data collection and analysis. Individual identity was concealed. All the data of patients were maintained in MEDIX medi- • Comorbidity-Age-Lymphocyte count-Lactate dehydrogenase score had a good area under the curve, the highest sensitivity of its cut-off value, required only 4 parameters, and is easy to calculate so it may be a better tool among the 3 scores in outcome prediction for COVID-19 patients.
• Age, platelet count, troponin T level, NEWS, SOFA, and CALL scores are found to be predictors of outcome in severe or critical hospitalized COVID-19 patients.
value of each score along with sensitivity, specificity, and positive and negative likelihood ratio was calculated by the Youden index (MedCalC software). This cut-off value was used to group the patients. Quantitative variables were compared by t-tests and qualitative variables were compared by chi-square tests. In the end, predictors of outcome in COVID-19 patients were further analyzed by Cox regression analysis.

Results
A total of 214 patients were admitted to the HDU and 203 patients (n = 203) were included after excluding 11 patients.
The primary aim of this study was to evaluate the efficacy of the different scoring systems in determining the outcome of patients with COVID-19 infection. Three scoring systems were evaluated, namely, NEWS, SOFA, and CALL score.
The vital signs, laboratory parameters, and modes of supplemental oxygen required by 203 patients in the study cohort of COVID-19 infection needed for the calculation of 3 scores (NEWS, SOFA, and CALL) are shown in Table 1.

ROC Curve for NEWS, SOFA, and CALL Score
The AUC calculated by ROC was used to determine the efficacy of each score as an outcome predictor in patients with COVID-19 infection.
Youden index was used to calculate the cut-off value for each score with sensitivity, specificity, positive likelihood ratio, and negative likelihood ratio. The AUC calculated by ROC of 3 scores (CALL, NEWS, and SOFA) to predict the outcome in patients with severe or critical COVID-19 patients is shown in Figure 1.  = 14), septic shock 6.4% (n = 13), and arrhythmias 2.9% (n = 6).
The study cohort was divided into 2 groups according to the cut-off value calculated by the Youden index. The cut-off value for NEWS

Supplemental oxygen
Oxygen  Table 3.
Regression analysis was used to determine the single determinants influencing the outcome of patients with COVID-19 infection. First, all variables were tested with univariate analysis then only those variables found to be predictors of outcome were further tested by multivariate analysis. Omnibus tests showed that the model was statistically fit for analysis (chi-square test = 29.87, P = .01) as the model covered 22%-34% variation of variables (Cox and Snell pseudo' s R 2 and Nagelkerke pseudo' s R 2 , respectively) and classified 75.4% of cases. Among quantitative variables, age, platelets, troponin T, NEWS, SOFA, and CALL scores were found to be statistically significant predictors of outcome while among qualitative variables, the presence of comorbid conditions and groups of NEWS, SOFA, and CALL scores according to cut-off value were found to be independent predictors of outcome of COVID-19 patients. The various predictors that had a statistically significant effect on the outcome of patients in the study cohort are shown in Table 4.

Discussion
It has been just a few months back that the World Health Organization declared COVID-19 as a pandemic on March 11, 2020. 1 Ever since then, it has tremendously burdened the health infrastructure with unmet medical demands and also crippling economics. The spectrum of COVID-19 ranges from mild symptoms to critical forms leading to increased morbidity and mortality. Early and appropriate selection of high-risk patients with poor outcomes is of paramount importance. This study focuses on determining the efficacy of the NEWS, SOFA, and CALL scores in determining the outcome of COVID-19.

NEWS Score
It was first developed in England in 2012 to replace the locally existing EWS and has now become a globally accepted tool. 15 For COVID-19 patients, the advantage of the NEWS score is the inclusion of more appropriate parameters including SpO 2 and respiratory indices. 12 It is a good predictor of mortality and deterioration both in prehospital and in-hospital setups. 16 In

SOFA Score
It was first developed in 1994 and encompasses diverse parameters of multiple organ systems. It is a widely validated tool for critical diseases, 19 but it is not acquired as quickly as the other 2 EWS because acquiring lab parameters takes time. The increasing score has a good correlation with increasing mortality. 20 In the context of COVID-19, the SOFA score also had an acceptable utility (AUC = 0.6) for outcome in a previous study. 21 In our study, similar results were obtained. The AUC of SOFA for prediction of the non-survived outcome is 0.72 and with a cut-off of 3, its sensitivity of 68.97%, and specificity of 67.42%. Although this sensitivity and specificity are slightly lower than the NEWS score, the AUC for the prediction of outcome is nearly the same for the NEWS and SOFA score (AUC = 0.78 vs. 0.72, P > .05). The mortality   .05). Similarly, only a trivial portion of patients, that is, 0.9% required invasive ventilation with a score <3 compared to 7.4% who required invasive ventilation with a score >3 (P < .05).

CALL Score
The CALL score has been devised as a means to anticipate disease progression in COVID-19.
Though it encompasses 4 simple parameters, it is unique as it does not take the respiratory parameters despite the fact that up to 15% of patients have florid respiratory involvement ranging from interstitial pneumonia to respiratory failure. 22 In our study, the AUC of the CALL score is 0.85. Similarly, another study done by Ji et al 11 found the CALL score as a novel scoring model to predict the outcome and outline the management plan for COVID-19 patients. They found an AUC of above 0.90 and at a cut-off value of 6, positive predictive value was around 50%, and a very high negative predictive value of nearly 99%. In our study, the cut-off value was calculated for the CALL score and it was 8. At this cut-off value, it has the highest sensitivity of 88.89% compared to the sensitivity of cut-off values for the NEWS and SOFA scores. Likelihood ratios for this cut value (8) were also significant with a positive likelihood ratio >1 (2.67) and a negative-positive likelihood ratio <1 (0.17) (P < .0001). This is evident from Table 3 which showed that the greater portion of patients required invasive ventilation and they died whose CALL score was >8.
In our study, AUC estimation showed that all 3 scoring systems performed well as outcome predictors in patients with COVID-19 but the CALL score outperformed the other 2 (AUC = 0.85). It is worth mentioning here that pairwise comparisons among these scores (CALL ~ NEWS, CALL ~ SOFA, and NEWS ~ SOFA) did not reveal that any of these 3 scoring systems are better than the others (P > .05), but as CALL score had AUC >0.80, its cut-off value has good sensitivity, it required only 4 parameters, and it is very easy to calculate, so CALL score may be a better tool among the 3 scoring systems in outcome prediction for moderate to severe COVID-19.
It has been observed that the presence of comorbid conditions has been associated with the unfavorable course for COVID-19 patients. In our study, 66.5% of patients had co-morbid conditions leading to increased severity of disease and more HDU admission. The commonest co-morbidity in our cohort was diabetes (52.2%) followed by hypertension, chronic kidney disease, and ischemic heart disease (44.8%, 12.3%, and 8.3%, respectively). The study by Tian et al 23 shows that 45% of severe COVID-19 patients had comorbidities. Other studies also show a similar proportion of comorbidities in patients with COVID-19. 24,25 In our study, patients of older age were at higher odds of a poor outcome (OR 1.15, P = .01). Furthermore, low platelets, high Trop-T, and the presence of co-morbidity are found as significant predictors of outcomes. Same observations have been made in other studies as well. [24][25][26][27] Similarly, the presence of comorbidities and high NEWS, SOFA, or CALL scores at the time of assessment also had a significant impact on the patient' s outcome (odds ratio = 1.21, 1.80, and 2.24, respectively).
Although it is a single-centered study and hence would greatly limit the generalizability of the results to other parts of the world, this study is among the first to determine the predictive efficacy and compare various COVID-19 severity scoring systems in moderate to severely affected patients.
In conclusion, all 3 scores (NEWS, SOFA, and CALL scores) are all good prognosticators to determine the outcome of patients with COVID-19 infection, but since the CALL score requires only 4 parameters and it is very easy to calculate, CALL score may be a better tool among the 3 scoring systems in outcome prediction for moderate to severe COVID-19. Until a specific COVID-19 score becomes available, these scores may be used to help identify highrisk patients and for the timely allocation of available medical resources.   Informed Consent: Written informed consent was obtained from all participants who participated in this study.
Author Acknowledgments: The authors would like to thank all the paramedical staff, house officers, post graduate trainees, registrars and consultants from all departments of Fauji Foundation Hospital, Rawalpindi who have performed their duties vigilantly, skillfully and with responsibility in HDU during COVID pandemic. The authors are thankful to MedCalc software limited, Ostend, Belgium for providing free MedCalc software that helped a lot in statistical analysis.

Declaration of Interests:
The authors have no conflict of interest to disclose.
Funding: The authors have no financial support to disclose.